Manager, GPU Accelerated Data Analytics

Nvidia

Confirmed live yesterday High trust

Hybrid

Quick summary

Work type: Hybrid
Location: Santa Clara, CANew York, NY
Salary: $224,000–$356,500 / yr
Employment: Full-time
Posted: 83 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $206k

This role $290k

$142k $380k

below market most similar roles pay here above market

This role pays more than 95% of similar roles. Most pay $176,450–$235,750 — the blue band above. At the midpoint, this role pays about $290k versus about $206k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 1623 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1110 roles with salary data.

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At a glance

TL;DR · Manager, GPU Accelerated Data Analytics

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The Manager, GPU Accelerated Data Analytics joins the Developer Technology Engineering team to lead a distributed group of performance engineers. This role involves researching and developing innovative techniques to optimize complex workloads across cloud and on-premise environments, specifically focusing on modernizing data centers by improving performance for databases, data preprocessing, compression, video transcoding, and web servers. You will drive software design decisions, influence architecture roadmaps, and mentor team members to strengthen external developer engagements. Key technical requirements include proficiency in C/C++, CUDA, and low-level performance optimization. Candidates must possess deep expertise in CPU and GPU architecture fundamentals, algorithms, and distributed high-performance data analytics, including SQL or vector databases. The work addresses the challenge of parallelizing difficult workloads to save cost and power using accelerated computing.

Skills

CUDA C++ C GPU Architecture Parallel Computing SQL Vector Databases Algorithms Performance Optimization Data Analytics Deep Learning Inference

What you'll do

Research and develop innovative techniques to optimize performance for complex workloads in cloud and on-premise environments.
Lead software design decisions and influence the hardware architecture roadmap.
Develop implementations to reduce costs and power consumption in modern data centers using NVIDIA platforms.
Build and mentor a distributed team of performance engineers to strengthen external developer engagements.
Prioritize and lead key initiatives that advance the performance and adoption of NVIDIA hardware and software.
Communicate technical solutions and strategic decisions to multi-functional teams and company leadership.
Advocate for next-generation hardware and software products that address the evolving needs of the developer community.

What we're looking for

MS or PhD in Computer Science, Computer Engineering, or a related computationally focused science degree (or equivalent experience).
4+ years of experience in a technical role.
3+ years of experience in an engineering leadership role.
Hands-on experience in low-level performance optimization, including GPU parallel programming such as CUDA.
Programming fluency in C/C++ with a deep understanding of algorithms and software development.
In-depth expertise with CPU and GPU architecture fundamentals.
Experience leading engineering teams to design performance-first prototypes (preferred).

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